Environments & Packages ======================= ARCH provides flexible tools to create isolated environments for Python, R, and multi-language workflows. By working within a virtual environment, users can install libraries, manage packages, and build reproducible projects without interfering with system-wide software. This section covers multiple environment types and how to connect them to common platforms: - **Virtual Environments** — Python venvs, Conda environments, and Spack packages - **Conda R** — Creating and managing R environments with Conda - **Link Conda to Jupyter** — Making your Conda environments available as Jupyter kernels - **Link Conda to RStudio** — Running RStudio Server sessions using a Conda-managed R Whether you're developing pure Python code, working with machine learning frameworks, managing R packages, or preparing complex HPC workflows, these guides will help you get set up correctly. Questions? Contact `help@arch.jhu.edu `__ for assistance. .. toctree:: :maxdepth: 1 Tutorial_Virtual_Envs Tutorial_Conda_R Tutorial_Conda_Jupyter Tutorial_Conda_Rstudio